Another Conjugate Gradient Algorithm with Guaranteed Descent and Conjugacy Conditions for Large-scale Unconstrained Optimization-Reference-Cited by-同舟云学术

Another Conjugate Gradient Algorithm with Guaranteed Descent and Conjugacy Conditions for Large-scale Unconstrained Optimization

Published:2013-02-21 Issue:1 Volume:159 Page:159-182
ISSN:0022-3239
Container-title:Journal of Optimization Theory and Applications
language:en
Short-container-title:J Optim Theory Appl

Author:

Andrei Neculai

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Management Science and Operations Research,Control and Optimization

Link

http://link.springer.com/content/pdf/10.1007/s10957-013-0285-9.pdf

Reference29 articles.

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2. O’Leary, D.P.: Conjugate gradients and related KMP algorithms: the beginnings. In: Adams, L., Nazareth, J.L. (eds.) Linear and Nonlinear Conjugate Gradient—Related Methods, pp. 1–8. SIAM, Philadelphia (1996)

3. Hager, W.W., Zhang, H.: A survey of nonlinear conjugate gradient methods. Pac. J. Optim. 2, 35–58 (2006)

4. Dolan, E.D., Moré, J.J.: Benchmarking optimization software with performance profiles. Math. Program. 91, 201–213 (2002)

5. Andrei, N.: An unconstrained optimization test functions collection. Adv. Model. Optim. 10, 147–161 (2008)

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